Rethinking the household: the impacts of transfers

Submitted by Markus Goldstein
On Wed, 02/26/2014

Two weeks ago, I blogged[1] about some productive impacts of cash transfer programs. For these effects, as well as the myriad other blog posts and papers on this topic out there, a key point is that the benefits of these transfers extend well beyond the actual individual recipient of the transfer.

But what if we entertain the possibility that those around the direct beneficiary are actually a shifting population, and what's more, a population that is shifting in direct response to the transfer? This raises significant issues for how we think about measuring the benefits of these transfers. A nice recent paper [2]by Amar Hamoudi and Duncan Thomas gives us some evidence as to why this might be an issue this using the South African Old Age Pension.

Let's start with the context. As Hamoudi and Thomas point out, the South African Old Age Pension (OAP) is a hefty transfer, weighing in at around $120 a month (as of 2000) -- about equal to the median income of employed black working age men. To qualify folks have to be over 60 for women and 65 for men (at the time of the analysis -- it's since changed) and have assets below a certain threshold (a criteria which most of the black population had no problem satisfying). As a result, in 2000, around 80% of eligible black women and 75% of eligible black men reported getting the OAP.

This program originally had racial gaps in the amount of the benefits, but with the end of apartheid, these were erased. And a host of papers looking at the impacts of this pension ensued, ranging from child nutrition in pension receiving households (here[3] and here[4]) to the displacement of remittances[5] (Hamoudi and Thomas have a nice comprehensive review). And as Hamoudi and Thomas point out, some of these papers raise issues of changing household composition. Indeed, a recent paper[6] by Ardington et. al. indicates that the substantial pension income may have financed outmigration from the pension households.

Hamoudi and Thomas tuck into this issue, asking how the composition of pension households might end up being different than those not getting the pension. Of course, the OAP wasn't randomized, but they use age eligibility as an instrument and put in a bunch of controls for household demographics. And for data, they use the 1998 DHS which not only was conducted soon after the OAP was extended to the whole black population, but also has some data on adult height and education -- which they are going to use to measure the human capital levels of individuals within households.

What do they find? In short, adults with lower human capital are more likely to be present in OAP recipient households. Men aged 20-55 have 1.02 years fewer schooling (12% of the average schooling) and women are 2.76 cm shorter (that's 1/3 of a standard deviation). And there is more of this negative selection in male pension-recipient households. There are also some effects for male children: 6-14 year old boys in pension households are 0.36 years behind the schooling of those in non-pension households.

If we focus on the negative selection of adults, what could be going on? Hamoudi and Thomas don't nail it down, but give us two theories to think about. First, it could be that the pensioner's bargaining power has gone up, and he or she demands more home-produced services. And the individuals with comparative advantage in these services come on home, and those with more human capital (and thus comparative advantage in the labor market) are not around. Or it could be a shift in family time allocation, with the higher human capital adults migrating.

The bottom line here is that when we think about evaluating these programs, we can't take the composition of the household as given. And this is something we should think about seriously when we think about benefits to folks other than the direct recipient of the transfer. Moreover, this goes beyond transfers. As Hamoudi and Thomas nicely put it we need to think about "moving beyond theory and data that is bound by the confines of a spatially-defined household to a broader conceptualization of the networks that play an important role in decisions about family life." We need to do this not only in our analysis, but also our data collection.